Manipulating and Perceiving Simultaneously (MAPS) for Haptic Object Recognition

这个SGER项目是对使用触觉信息进行操作和识别的算法的可行性研究。操作和感知同时(MAP)范式借鉴了同步定位和地图(SLAM)和视觉对象识别的最新进展，并对其进行了必要的修改，使其适应于触觉探索。在地图中，探索是由定位具有关于对象的高信息含量的“感兴趣区域”的目标驱动的。这些兴趣点的触觉特性将以独立于坐标系的方式与位置信息一起编码。在学习阶段，将获取大量这样的点并将其存储在数据库中。在识别过程中，新获得的点将与数据库中的点进行比较，以生成可信的模型假设。最终的识别决策还将纳入表面结构的位置和方向中隐含的几何约束。这项计划的主要贡献将是：-开发主动探索策略，以提取、定位和绘制独特的表面特征；-开发和评估基于触觉的物体识别算法，使用空间和触觉“外观”信息；-开发一个实验环境，以实施和评估地图算法。

This SGER project is a feasibility study of algorithms for manipulation and recognition using haptic information. The Manipulation-and-Perceiving-Simultaneously (MAPS) paradigm borrows key ideas from recent advances in simultaneous localization and mapping (SLAM) and visual object recognition with modifications necessary to adapt them to haptic exploration.In MAPS, exploration is driven by the objective of locating "interest areas" that carry high information content about the object. The haptic properties of these interest points will be encoded, together with location information, in a coordinate-system independent fashion. During a learning phase, a large set of such points will be acquired and stored in a database. During recognition, newly acquired points will be compared with those in the database to generate plausible model hypotheses. The final recognition decision will also incorporate the geometric constraints implicit in the location and orientation of the surface structure.The key contributions of this project will be:- The development of active exploration strategies to extract, localize and map distinctive surface features;- The development and evaluation of haptics-based object recognition algorithms using both spatial and haptic "appearance" information; - The development of an experimental environment to implement and evaluate MAPS algorithms.